Dataset Information

Unrelated Fungal Rust Candidate Effectors Act on Overlapping Plant Functions.

ABSTRACT: Rust fungi cause epidemics that threaten the production of important plant species, such as wheat and soy. Melampsora larici-populina (Mlp) causes the poplar rust and encodes at least 1184 candidate effectors (CEs) whose functions are poorly known. In this study, we sequenced the transcriptome and used mass spectrometry to analyze the metabolome of Arabidopsis plants constitutively expressing 14 Mlp CEs and of a control line to discover alterations leading to plant susceptibility. We found 2299 deregulated genes across the experiment. Genes involved in pattern-triggered immunity, such as FRK1, PR1, RBOHD, and WRKY33, as well as AUX/IAA genes were down-regulated. We further observed that 680 metabolites were deregulated in at least one CE-expressing transgenic line, with "highly unsaturated and phenolic compounds" and "peptides" enriched among down- and up-regulated metabolites. Interestingly, transgenic lines expressing unrelated CEs had correlated patterns of gene and metabolite deregulation, while expression of CEs belonging to the same family deregulated different genes and metabolites. Thus, our results uncouple effector sequence similarity and function. This supports that effector functional investigation in the context of their virulence activity and effect on plant susceptibility requires the investigation of the individual effector and precludes generalization based on sequence similarity.

SUBMITTER: Dos Santos KCG

PROVIDER: S-EPMC8148019 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Unrelated Fungal Rust Candidate Effectors Act on Overlapping Plant Functions.

Dos Santos Karen Cristine Goncalves KCG Pelletier Gervais G Séguin Armand A Guillemette François F Hawkes Jeffrey J Desgagné-Penix Isabel I Germain Hugo H

Microorganisms 20210505 5

Rust fungi cause epidemics that threaten the production of important plant species, such as wheat and soy. Melampsora larici-populina (Mlp) causes the poplar rust and encodes at least 1184 candidate effectors (CEs) whose functions are poorly known. In this study, we sequenced the transcriptome and used mass spectrometry to analyze the metabolome of Arabidopsis plants constitutively expressing 14 Mlp CEs and of a control line to discover alterations leading to plant su ...[more]

PMID: 34063040

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Project description:Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i) contain a secretion signal, (ii) are encoded by in planta induced genes, (iii) have similarity to haustorial proteins, (iv) are small and cysteine rich, (v) contain a known effector motif or a nuclear localization signal, (vi) are encoded by genes with long intergenic regions, (vii) contain internal repeats, and (viii) do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components.

Project description:Current models of plant-pathogen interactions stipulate that pathogens secrete effector proteins that disable plant defense components known as virulence targets. Occasionally, the perturbations caused by these effectors trigger innate immunity via plant disease resistance proteins as described by the "guard hypothesis." This model is nicely illustrated by the interaction between the fungal plant pathogen Cladosporium fulvum and tomato. C. fulvum secretes a protease inhibitor Avr2 that targets the tomato cysteine protease Rcr3(pim). In plants that carry the resistance protein Cf2, Rcr3(pim) is required for resistance to C. fulvum strains expressing Avr2, thus fulfilling one of the predictions of the guard hypothesis. Another prediction of the guard hypothesis has not yet been tested. Considering that virulence targets are important components of defense, different effectors from unrelated pathogens are expected to evolve to disable the same host target. In this study we confirm this prediction using a different pathogen of tomato, the oomycete Phytophthora infestans that is distantly related to fungi such as C. fulvum. This pathogen secretes an array of protease inhibitors including EPIC1 and EPIC2B that inhibit tomato cysteine proteases. Here we show that, similar to Avr2, EPIC1 and EPIC2B bind and inhibit Rcr3(pim). However, unlike Avr2, EPIC1 and EPIC2B do not trigger hypersensitive cell death or defenses on Cf-2/Rcr3(pim) tomato. We also found that the rcr3-3 mutant of tomato that carries a premature stop codon in the Rcr3 gene exhibits enhanced susceptibility to P. infestans, suggesting a role for Rcr3(pim) in defense. In conclusion, our findings fulfill a key prediction of the guard hypothesis and suggest that the effectors Avr2, EPIC1, and EPIC2B secreted by two unrelated pathogens of tomato target the same defense protease Rcr3(pim). In contrast to C. fulvum, P. infestans appears to have evolved stealthy effectors that carry inhibitory activity without triggering plant innate immunity.

Project description:BackgroundRust fungi constitute the largest group of plant fungal pathogens. However, a paucity of data, including genomic sequences, transcriptome sequences, and associated molecular markers, hinders the development of inhibitory compounds and prevents their analysis from an evolutionary perspective. Gymnosporangium yamadae and G. asiaticum are two closely related rust fungal species, which are ecologically and economically important pathogens that cause apple rust and pear rust, respectively, proved to be devastating to orchards. In this study, we investigated the transcriptomes of these two Gymnosporangium species during the telial stage of their lifecycles. The aim of this study was to understand the evolutionary patterns of these two related fungi and to identify genes that developed by selection.ResultsThe transcriptomes of G. yamadae and G. asiaticum were generated from a mixture of RNA from three biological replicates of each species. We obtained 49,318 and 54,742 transcripts, with N50 values of 1957 and 1664, for G. yamadae and G. asiaticum, respectively. We also identified a repertoire of candidate effectors and other gene families associated with pathogenicity. A total of 4947 pairs of putative orthologues between the two species were identified. Estimation of the non-synonymous/synonymous substitution rate ratios for these orthologues identified 116 pairs with Ka/Ks values greater than1 that are under positive selection and 170 pairs with Ka/Ks values of 1 that are under neutral selection, whereas the remaining 4661 genes are subjected to purifying selection. We estimate that the divergence time between the two species is approximately 5.2 Mya.ConclusionThis study constitutes a de novo assembly and comparative analysis between the transcriptomes of the two rust species G. yamadae and G. asiaticum. The results identified several orthologous genes, and many expressed genes were identified by annotation. Our analysis of Ka/Ks ratios identified orthologous genes subjected to positive or purifying selection. An evolutionary analysis of these two species provided a relatively precise divergence time. Overall, the information obtained in this study increases the genetic resources available for research on the genetic diversity of the Gymnosporangium genus.

Project description:Fungal effector proteins are important in mediating disease infections in agriculturally important crops. These secreted small proteins are known to interact with their respective host receptor binding partners in the host, either inside the cells or in the apoplastic space, depending on the localisation of the effector proteins. Consequently, it is important to understand the interactions between fungal effector proteins and their target host receptor binding partners, particularly since this can be used for the selection of potential plant resistance or susceptibility-related proteins that can be applied to the breeding of new cultivars with disease resistance. In this study, molecular docking simulations were used to characterise protein-protein interactions between effector and plant receptors. Benchmarking was undertaken using available experimental structures of effector-host receptor complexes to optimise simulation parameters, which were then used to predict the structures and mediating interactions of effector proteins with host receptor binding partners that have not yet been characterised experimentally. Rigid docking was applied for both the so-called bound and unbound docking of MAX effectors with plant HMA domain protein partners. All bound complexes used for benchmarking were correctly predicted, with 84% being ranked as the top docking pose using the ZDOCK scoring function. In the case of unbound complexes, a minimum of 95% of known residues were predicted to be part of the interacting interface on the host receptor binding partner, and at least 87% of known residues were predicted to be part of the interacting interface on the effector protein. Hydrophobic interactions were found to dominate the formation of effector-plant protein complexes. An optimised set of docking parameters based on the use of ZDOCK and ZRANK scoring functions were established to enable the prediction of near-native docking poses involving different binding interfaces on plant HMA domain proteins. Whilst this study was limited by the availability of the experimentally determined complexed structures of effectors and host receptor binding partners, we demonstrated the potential of molecular docking simulations to predict the likely interactions between effectors and their respective host receptor binding partners. This computational approach may accelerate the process of the discovery of putative interacting plant partners of effector proteins and contribute to effector-assisted marker discovery, thereby supporting the breeding of disease-resistant crops.

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Unrelated Fungal Rust Candidate Effectors Act on Overlapping Plant Functions.

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Unrelated Fungal Rust Candidate Effectors Act on Overlapping Plant Functions.

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